Exploring a Toll Auction Mechanism Enabled by Vehicle-to-Infrastructure Technology

High-occupancy toll (HOT) lanes—an increasingly popular solution for congested roadway networks—give drivers the option to access express lanes. The cost of entry often varies with demand, although no standard method of optimizing these price points exists. Using the principles of a Vickrey auction that incentivizes true-value bids, this paper proposes a tolling system that uses vehicle-to-infrastructure technology to optimize toll operator revenue with HOT lane usage. In the scenario, a roadway network consists of a HOT lane and a general-purpose lane, each with identical physical properties. Drivers can access the HOT lane at the start of the facility or at one interim point along the roadway. With the use of a triangular distribution to approximate the distribution of travelers’ value of time (VOT), the model explores the impact of varying the distribution’s mode on revenue earned by the toll operator. Results from the model indicate that when the toll operator maximizes the model’s revenue, the percentage of auction bids accepted for toll road access is robust to changes in the VOT distribution. This percentage equates to approximately 17% of vehicles accessing the facility. Given the difficulty in obtaining actual travelers’ distribution of VOT, this auction tolling mechanism implies that obtaining an exact VOT distribution may not be necessary for this type of tolling analysis

HOT Lanes with a Refund Option and Potential Application of Connected Vehicles

abstract: Priced Managed Lanes (MLs) have been increasingly advocated as one of the effective ways to mitigating congestion in recent years. This study explores a new and innovative pricing strategy for MLs called Travel Time Refund (TTR). The proposed TTR provides an additional option to paying drivers that insures their travel time by issuing a refund to the toll cost if they do not reach their destination within specified travel times due to accidents or other unforeseen circumstances. Perceived benefits of TTR include raised public acceptance towards priced MLs, utilization increase of HOV/HOT lanes, overall congestion mitigation, and additional funding for relevant transportation agencies. To gauge travelers’ interests of TTR and to analyse its possible impacts, a stated preference (SP) survey was performed. An exploratory and statistical analysis of the survey responses revealed negative interest towards HOT and TTR option in accordance with common wisdom and previous studies. However, it is found that travelers are less negative about TTR than HOT alone; supporting the idea, that TTR could make HOT facilities more appealing. The impact of travel time reliability and latent variables representing psychological constructs on travelers’ choices in response to this new pricing strategy was also analysed. The results indicate that along with travel time and reliability, the decision maker’s attitudes and the level of comprehension of the concept of HOT and TTR play a significant role in their choice making. While the refund option may be theoretically and analytically feasible, the practical implementation issues cannot be ignored. This study also provides a discussion of the potential implementation considerations that include information provision to connected and non-connected vehicles, distinction between toll-only and refund customers, measurement of actual travel time, refund calculation and processing and safety and human factors issues. As the market availability of Connected and Automated Vehicles (CAVs) is prognosticated by 2020, the potential impact of such technologies on effective demand management, especially on MLs is worth investigating. Simulation analysis was performed to evaluate the system performance of a hypothetical road network at varying market penetration of CAVs. The results indicate that Connected Vehicles (CVs) could potentially encourage and enhance the use of MLs.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

A Model-based Dynamic Toll Pricing Strategy for Controlling Highway Traffic

A model-based approach to dynamic toll pricing has been developed to provide a systematic method for determining optimal freeway pricing schemes. A novel approach is suggested for alleviating congestion, which utilizes identified models of driver behavior and traffic flow, as well as optimization of the target density to maximize throughput. Real-time traffic information from on-road sensors is integrated with historical information to provide feedback and preview for the dynamic toll price controller. The algorithm developed here provides an opportunity to improve on existing toll policy by guaranteeing minimum speeds for toll lane drivers, maintaining consistent traffic flow for the other drivers, and optimizing the overall traffic throughputthe Ford-MIT Allianc

Social Equity Impacts of Congestion Management Strategies

This white paper examines the social equity impacts of various congestion management strategies. The paper includes a comprehensive list of 30 congestion management strategies and a discussion of equity implications related to each strategy. The authors analyze existing literature and incorporate findings from 12 expert interviews from academic, non-governmental organization (NGO), public, and private sector respondents to strengthen results and fill gaps in understanding. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework (Shaheen et al., 2017) to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular congestion mitigation measure. The congestion management strategies discussed are grouped into six main categories, including: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation. The findings show that the social equity impacts of certain congestion management strategies are not well understood, at present, and further empirical research is needed. Congestion mitigation measures have the potential to affect travel costs, commute times, housing, and accessibility in ways that are distinctly positive or negative for different populations. For these reasons, social equity implications of congestion management strategies should be understood and mitigated for in planning and implementation of these strategies

Dynamic Modeling for Intelligent Transportation System Applications

Special Issue on Dynamic Modeling for Intelligent Transportation System Applicationspostprin

Assessing the effectiveness of managed lane strategies for the rapid deployment of cooperative adaptive cruise control technology

Connected and Automated Vehicle (C/AV) technologies are fast expanding in the transportation and automotive markets. One of the highly researched examples of C/AV technologies is the Cooperative Adaptive Cruise Control (CACC) system, which exploits various vehicular sensors and vehicle-to-vehicle communication to automate vehicular longitudinal control. The operational strategies and network-level impacts of CACC have not been thoroughly discussed, especially in near-term deployment scenarios where Market Penetration Rate (MPR) is relatively low. Therefore, this study aims to assess CACC\u27s impacts with a combination of managed lane strategies to provide insights for CACC deployment. The proposed simulation framework incorporates 1) the Enhanced Intelligent Driver Model; 2) Nakagami-based radio propagation model; and 3) a multi-objective optimization (MOOP)-based CACC control algorithm. The operational impacts of CACC are assessed under four managed lane strategies (i.e., mixed traffic (UML), HOV (High Occupancy Vehicle)-CACC lane (MML), CACC dedicated lane (DL), and CACC dedicated lane with access control (DLA)). Simulation results show that the introduction of CACC, even with 10% MPR, is able to improve the network throughput by 7% in the absence of any managed lane strategies. The segment travel times for both CACC and non-CACC vehicles are reduced. The break-even point for implementing dedicated CACC lane is 30% MPR, below which the priority usage of the current HOV lane for CACC traffic is found to be more appropriate. It is also observed that DLA strategy is able to consistently increase the percentage of platooned CACC vehicles as MPR grows. The percentage of CACC vehicles within a platoon reaches 52% and 46% for DL and DLA, respectively. When it comes to the impact of vehicle-to-vehicle (V2V), it is found that DLA strategy provides more consistent transmission density in terms of median and variance when MPR reaches 20% or above. Moreover, the performance of the MOOP-based cooperative driving is examined. With average 75% likelihood of obtaining a feasible solution, the MOOP outperforms its counterpart which aims to minimize the headway objective solely. In UML, MML, and DL strategy, the proposed control algorithm achieves a balance spread among four objectives for each CACC vehicle. In the DLA strategy, however, the probability of obtaining feasible solution falls to 60% due to increasing size of platoon owing to DLA that constraints the feasible region by introduction more dimensions in the search space. In summary, UML or MML is the preferred managed lane strategy for improving traffic performance when MPR is less than 30%. When MRP reaches 30% or above, DL and DLA could improve the CACC performance by facilitating platoon formation. If available, priority access to an existing HOV lane can be adopted to encourage adaptation of CACC when CACC technology becomes publically available

Potential Categories for the Application of Blockchain in Intelligent Transportation Systems (ITS)

693JJ321D000021 Task Order 693JJ322F00408NThe purpose of this document is to summarize for the United States Department of Transportation\u2019s (U.S. DOT\u2019s) Intelligent Transportation Systems Joint Program Office (ITS JPO), the potential blockchain applications in ITS categorized based on Architecture Reference for Cooperative and Intelligent Transportation (ARC-IT) taxonomy. The applications are selected based on the literature review of existing blockchain applications, conceptual use cases and pilot projects; relevance with U.S. DOT\u2019s strategic goals and research and development plans; and inputs from U.S. DOT

Agent-Based Models of Highway Investment Processes: Forecasting Future Networks under Public and Private Ownership Regimes

The present highway funding system, especially fuel taxes, may become a less reliable revenue source in the future, while the transportation public agencies do not have sufficient financial resources needed to meet the increasing traffic demand. In the last two decades there has been increasing interest in utilizing private sector to develop, finance and operate new and existing roadways in the United States. While transportation privatization projects have shown signs of success, it is not always clear how to measure the true benefits associated with these projects for all stakeholders, including the public sector, the private sector and the public. "Win-win" privatization agreements are tricky to make due to conflicting nature of the various stakeholders involved. Therefore, there is a huge need to study the welfare impacts of various road privatization arrangements for the society as a whole, and the financial implications for private investors and public road authorities. In order to address these needs, first, an empirical analysis is performed to study the investment decision processes of public transportation agencies. Second, the agent-based decision-making model is developed to consider transportation investment processes at different levels of government which forecasts future transportation networks and their performance under both existing and alternative transportation planning processes. Third, various highway privatization schemes currently practiced in the U.S. are identified and an agent-based model for analyzing regulatory policies on private-sector transportation investments is developed. Fourth, the above mentioned models are demonstrated on the networks with grid and beltway topologies to study the impacts of topology configuration on the privatization arrangements. Based on the simulation results of developed models, a number of insights are provided about impacts of ownership structures on the socio-economic performance in transportation systems and transportation network changes over time. The proposed models and the approach can be used in long-run prediction of economic performance intended for describing a general methodology for transportation planning on large networks. Therefore, this research is expected to contribute significantly to the understanding and selecting proper road privatization programs on public networks

Financial Evaluation Of Milege Based User Fees For Florida\u27s Transportation Funding

Motor fuel taxes have been collected as a principal source of highway funding for close to a century. They account for approximately two thirds of all the highway user fees and about half of all highway expenditures. Federal fuel taxes have not kept pace with the inflation in general and increasing traffic demand and resulting construction, maintenance and operation costs of the transportation assets in particular. Lack of political will, combined with rising anti-tax sentiment among the populace, has kept the federal tax level not only well below its initial intents, but also at a unsustainable level in future. Mileage based user fees are possibly an alternative to the fuel taxes, which have been the main mechanism for funding the transportation system. Mileage based user fees have been successfully utilized in many parts of the world with glowing results. Germany‟s “TollCollect”, a quasi government enterprise has utilized GPS technology in collecting the users‟ fee from the truck operators. The system has been a financial engine providing much needed funding for many major transportation projects. Oregon Department of Transportation, in a federally co-funded pilot project, examined the practicality of the mileage based user fee collection at the fuel pumps. According to the Oregon study, there are not any major technical difficulties in mileage based user fee collection at the pump. Study participants (general motorist) did not express any objection to the mileage based user fee collection. This dissertation evaluates revenue impacts of several pricing policies including: Current per gallon fuel taxes, conversion to a mileage based user fee, time of day user fee application, iv area type user fee and congestion priced user fees. State of Florida‟s years 2015-2035 fuel revenue forecast is used as a case study. A model is constructed to estimate annual vehicle miles travelled for the analyses period. Fuel efficiencies, current per gallon fuel taxes and their corresponding mileage-based user fee equivalents are the input to a financial model developed for comparisons. Results demonstrate that decrease in fuel revenues due to vehicles fuel efficiency improvements can be offset by replacing current per gallon fuel taxes with a mileage-based user fee. Pricing the user fee according to area type, roadway classification, time of day and congestion level can not only generate more revenues but also assist in demand management